A primary obstacle capturing high-quality images is the lack of light. In low-light situations, such as capturing images in indoor environments or at night, the scene as a whole may provide insufficient light. Images of outdoor daylight scenes may also suffer from insufficient light in shady areas of the scene. Although there are various accessories that can be used to gather more light, such a larger-aperture lens, additional image sensors, image stabilization equipment, flash equipment, and so on, imaging devices with smaller form factors are unable to accommodate this equipment. For example, if the image capture device is a cell phone or wearable device, size constraints preclude inclusion of these large accessories.
Alternate strategies to improving image quality in low-light situations include increasing the exposure time of a camera or image sensor to increase pixel brightness. However, longer exposure times increase the presence of motion blur in an image that results from camera jitter or motion of a subject in the scene during image capture. In order to account for dark and noisy images, various techniques combine multiple image frames of a scene to produce a single image using pixel values from the multiple image frames. Combining multiple image frames into a single image reduces an overall amount of image noise, but it does not entirely eliminate image noise and often results in a visually soft image. Although there are various post-processing techniques that can be applied to improve visual qualities of a multiple-frame image, these post-processing techniques do not account for variations in a number of frames used to generate a multiple-frame image. Thus, it is desirable to visually alter images generated from multiple frames to produce a sharp image with minimal noise in a manner that considers an amount of frames used to generate an image.